HiDeF

HiDeF resolves hierarchical structures in biological networks by combining multiscale community detection and persistent homology to identify robust multiscale communities for the analysis of 'omics datasets.

Key Features:

• Multiscale Community Detection: Employs methods to identify communities at multiple scales within networks to capture varying levels of organization.
• Persistent Homology: Integrates persistent homology from mathematical topology to detect structures that are robust across scales.
• Application to Single-cell Transcriptomes: Has been applied to mouse single-cell transcriptomes to expand the catalog of identified cell types.
• Protein Interaction Analysis: Applied to protein interaction networks, including analysis of SARS-CoV-2 protein interactions suggesting potential hijacking of the WNT signaling pathway.

Scientific Applications:

• Single-cell Transcriptomics: Enhances resolution of cell type identification by identifying hierarchical community structures across scales.
• Protein Network Analysis: Reveals multiscale interaction modules and potential host–pathogen mechanisms in protein interaction networks.

Methodology:

Combines multiscale community detection with persistent homology to identify hierarchical network structures and persistent communities across scales.